WPS3736
Distortions to world trade: impacts on
agricultural markets and farm incomes
Kym Anderson, Will Martin and Dominique van der Mensbrugghe
World Bank
1818 H Street NW
Washington DC 20433
kanderson@worldbank.org
wmartin1@worldbank.org
dvandermensbrugg@worldbank.org
World Bank Policy Research Working Paper 3736, October 2005
The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the
exchange of ideas about development issues. An objective of the series is to get the findings out quickly,
even if the presentations are less than fully polished. The papers carry the names of the authors and should
be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely
those of the authors. They do not necessarily represent the view of the World Bank, its Executive Directors,
or the countries they represent. Policy Research Working Papers are available online at
http://econ.worldbank.org.
This is a product of the World Bank's pair of projects on Agricultural Trade Reform and the
Doha Development Agenda and on Putting Development Back into the Doha Agenda:
Poverty Impacts of a WTO Agreement. Chapters for the two books to be published in late
2005 can be downloaded at www.worldbank.org/trade/wto. The authors are grateful for helpful
comments from project participants and for funding from the UK and Dutch governments.
Abstract
This paper provides estimates of the impact that removing all merchandise trade
distortions (including agricultural subsidies) would have on food and agricultural
production, trade and incomes. Using the latest versions of the GTAP database and the
World Bank's LINKAGE model of the global economy (projected to 2015), our results
suggest farm employment, the real value of agricultural output and exports, the real
returns to farm land and unskilled labor, and real net farm incomes would all rise
substantially in developing country regions with a move to free merchandise trade,
thereby alleviating rural poverty ­ despite the decline in international terms of trade for
developing countries that are net food importers or are enjoying preferential access to
agricultural markets of high-income countries.
JEL codes: C68, D58, F17, Q17
Key words: Trade policy reform, computable general equilibrium modeling, agricultural
markets, economic welfare
Contact author:
Kym Anderson
Development Research Group
The World Bank
Mailstop MC3-303
1818 H Street NW
Washington DC 20433 USA
Phone +1 202 473 3387
Fax +1 202 522 1159
kanderson@worldbank.org
ii
Distortions to world trade: impacts on
agricultural markets and farm incomes
To what extent are government trade and subsidy policies still distorting agricultural
markets and farmers' incentives around the world? Nearly two decades ago a major World Bank
study addressed that question for 18 developing countries (Krueger, Schiff and Valdes 1988),
and found that farmers in those countries were discriminated against by their governments'
policies, albeit less so directly than indirectly (via restrictions on imports of industrial products
and overvalued exchange rates). Another study at that time focused on time series data for
developed and newly industrializing countries, and found a tendency for national governments to
gradually change from taxing to subsidizing agricultural relative to industrial production (and
from subsidizing to taxing food consumers) in the course of their economic development, and at
an earlier stage the weaker an economy's comparative advantage in agriculture (Anderson and
Hayami 1986).
Meanwhile the OECD Secretariat has been estimating direct producer supports by its
member governments, and finds that they all support their farmers and that the aggregate degree
of support is high and has not fallen over the past fifteen years (Legg 2003, OECD 2005) ­
having risen substantially over earlier post-World War II decades when manufacturing protection
rates began falling to what are now very low levels in those countries.
That is, developing countries' policies of the past had caused international prices of farm
products to be above what they otherwise would have been, while the policies of high-income
countries had the opposite effect. A partial equilibrium attempt to measure the net effect of those
policies in the 1980s suggests they almost exactly offset each other in terms of their impact on
international prices of temperate foods, while more than halving the volume of international food
trade (Tyers and Anderson 1992, Table 6.9). Hence developing country farmers and agricultural
production at that time were clearly discriminated against by the patterns of distortions across
sectors and regions.
Since the 1980s, however, a number of major policy changes have occurred. Many
developing countries have been reforming their trade and subsidy regimes unilaterally;
innumerable preferential trading arrangements (some reciprocal, others non-reciprocal) have
been signed and have led to sub-global or discriminatory trade liberalization that may or may not
have improved global welfare; the Uruguay Round of multilateral trade negotiations, begun in
1986, came to a successful conclusion in 1994 and by end-2004 the agreed reforms were fully
implemented; and the World Trade Organization (WTO) came into being to replace the GATT
Secretariat on 1 January 1995 and since then its membership has grown by 20 to almost 150
customs territories, with new members (especially China) committing to significant reforms as
the price of admission (Crawford and Fiorentino 2005; World Bank 2002, 2004, 2005; Drabek
and Bacchetta 2004).
By the mid-1990s it appeared to one group of analysts that, for the sample of fifteen
developing countries they examined, the problem of an anti-agricultural bias in those countries'
trade and sectoral policies had all but disappeared (Jensen, Robinson and Tarp 2002). But what
about in other developing countries? And are some developing countries overshooting and
adopting the potentially equally wasteful agricultural protectionist stance of more-advanced
economies?
2
To answer these questions requires extending the time series of estimates of distortions in
the Krueger/Schiff/Valdes sample and extending the sample to a wider range of countries. That
is the focus of a new research project getting under way at the World Bank. But in the meantime
it is possible to answer the question in the title of the present paper using a new database for
2001. Specifically, here we address the question: What would be the consequences for
agricultural markets and farm incomes if all countries were to reduce their trade distortions
simultaneously (as in an ambitious WTO round), as distinct from just reducing their own
distortions?1
That is, the aim of this paper is to make use of a new database and a global general
equilibrium model to assess how agricultural markets and value added in agriculture would
change if, over the next decade, the world were to remove all merchandise trade barriers and
agricultural subsidies. While no-one anticipates such a radical reform, the analysis serves as a
benchmark to suggest what is at stake in the WTO's current round of multilateral trade
negotiations ­ as well as in further unilateral reforms. It can also give a better indication of
agricultural comparative advantages around the world than is available by looking at indicators
in the current distortion-ridden situation.
Specifically, we make use of the World Bank's recursive dynamic model of the global
economy known as LINKAGE (van der Mensbrugghe 2004), which has formed the basis for the
World Bank's standard decade-long projections of the global economy and of its earlier trade
analysis (e.g., World Bank 2002, 2004). The distinction is made in our welfare results between
1 The Krueger, Schiff and Valdes (1988) and Jensen, Robinson and Tarp (2002) studies focused on effects of just
own-country policies, the first using partial equilibrium and the second using national general equilibrium
models. On the relationship between those two methodologies, see Bautista, Robinson, Wobst and Tarp (2001).
3
effects of moving to free trade by developing countries versus by high-income countries, and in
agriculture as compared with non-agricultural sectors. We also make use of the latest GTAP
database (Version 6.05, see www.gtap.org) which has the virtue of including not only reciprocal
but also non-reciprocal preferential tariffs, the latter providing low-income exporters duty-free
access to protected high-income country markets. This allows us to take into account the fact that
reform may cause a decline in the international terms of trade for those developing countries that
are enjoying preferential access to agricultural markets of high-income countries (in addition to
those that are net food importers because their comparative advantage is in other sectors such as
labor-intensive manufacturing).
The paper begins with an examination of current distortions, the emphasis being mainly
on import tariffs since they are later shown to be far more important than agricultural subsidies.
This is followed by a description of the LINKAGE model of the global economy to be used to
analyze the consequences of removing those distortions. The key results of the simulations are
then presented. After discussing some qualifications, the paper concludes by highlighting the key
messages and drawing out implications for developing countries in particular.
Key distortions in global markets
Border measures traditionally have been the main means by which governments distort
prices in their domestic markets for products, with the price of tradables relative to nontradables
affected by interventions in the market for foreign exchange, and the relative prices of the
various tradables affected by trade taxes-cum-subsidies or quantitative trade restrictions.
Multiple exchange rates have also altered relative prices among tradable products. Product-
4
specific domestic producer or consumer subsidies have played a more limited role (because of
their much greater cost to the treasury), with a few exceptions most notably in rich-country
agriculture. With the freeing up of most foreign exchange markets over the past two decades, the
phasing out of most export taxes,2 and the conversion of many non-tariff trade barriers into
tariffs, the task of measuring the extent of distortions to goods markets is made much easier in
that attention can focus on import tariffs and agricultural subsidies. In principle services trade
and foreign investment distortions also could distort incentives in the agricultural and industrial
sectors, but they are ignored here partly because much controversy still surrounds their
measurement and how they should be modelled, and partly because they do not seem destined
for major reform under the current Doha Development Agenda of multilateral trade reform by
WTO members.
The latest release of the GTAP dataset, Release 6.05, includes estimates of bilateral
tariffs and of domestic and export subsidies as of 2001 for 87 countries and country groups
spanning the world. This is a substantial improvement over Version 5 of the GTAP dataset,
which relates to 1997. The new protection data come from a joint CEPII (Paris)/ITC (Geneva)
project. The product of this joint effort, known as MAcMaps, is a HS6 tariff level detailed
database on bilateral protection that integrates trade preferences, specific and compound tariffs
and a partial evaluation of non-tariff barriers such as tariff rate quotas (TRQs).3 The new GTAP
database has lower tariffs than the previous database. This is because of the inclusion of bilateral
trade preferences, as well as the major reforms between 1997 and 2001 such as continued
2 Apparently only a few minor export taxes remain ­ see Piermartini (2004) and also Thiele (2004).
3 More information on the MAcMaps database is available in Bouët et al. (2004) and at
http://www.cepii.fr/anglaisgraph/bdd/macmap.htm. For details of its incorporation into the GTAP Version 6
dataset, see www.gtap.org.
5
implementation of the Uruguay Round agreements, and China's progress towards WTO
accession (which alone contributed to the ratio of global exports plus imports to GDP rising from
44 to 46 percent over those four years).
According to this dataset, the average import tariff for agriculture and food in 2001 was
16.0 percent for high-income countries and 17.7 percent for developing countries, while for
manufactures other than textiles and clothing it was 8.3 percent for developing countries and just
1.3 percent for high-income countries (Table 1). The averages of course obscure large variations
across countries and commodities, and are poor indicators of overall assistance to farming. For
example, if high-income countries' tariffs on temperate farm products are at a near-prohibitive
100 percent, but zero on tropical products such as coffee, those countries' import-weighted
average agricultural tariff could be quite low even though agricultural value added in those rich
countries had been enhanced substantially. Consider also the case of a developing country with a
strong agricultural comparative advantage in all but one small farming industry, and with high
tariffs to stave off import competition for that industry and for all manufacturing industries.
Overall agricultural value added would be depressed by that structure of protection, yet the
import-weighted average tariff protection for agriculture would be high and possibly above that
for manufactures. A third case is where the non-agricultural primary sector receives a similar
level of import protection as the farm sector and less than the manufacturing sector, but is much
more export-focused: trade reform may cause it to expand at the expense not only of
manufacturing but also of farming. Hence it is not possible to say from the tariff data in Table 1
whether developing country policies have overshot in terms of moving away from an anti-
agricultural bias, even though the ratio of agricultural to all goods tariffs in that table is well
above unity for each of the regions shown. What is needed to address that issue is a general
6
equilibrium model to estimate the net effects of all sectors' distortions on agricultural markets
and net farm income, to which we now turn.
The global LINKAGE model for assessing sectoral and welfare effects of trade distortions
The model used for this analysis is the World Bank's global dynamic computable general
equilibrium (CGE) model, known as LINKAGE (van der Mensbrugghe 2004). It is a relatively
straightforward CGE model but with some characteristics that distinguish it from standard
comparative static models such as the GTAP model (described in Hertel 1997). A key difference
is that it is recursive dynamic, so while it starts with 2001 as its base year it can be solved
annually through to 2015. The dynamics are driven by exogenous population and labor supply
growth, savings-driven capital accumulation, and labor-augmenting technological progress as
assumed for the Global Economic Prospects report in World Bank (2005). In any given year,
factor stocks are fixed. Producers minimize costs subject to constant returns to scale production
technology, consumers maximize utility, and all markets ­ including for labor ­ are cleared with
flexible prices. There are three types of production structures. Crop sectors reflect the
substitution possibilities between extensive and intensive farming; livestock sectors reflect the
substitution possibilities between pasture and intensive feeding; and all other sectors reflect
standard capital/labor substitution (with two types of labor: skilled and unskilled). There is a
single representative household per modeled region, allocating income to consumption using the
extended linear expenditure system. Trade is modeled using a nested Armington structure in
which aggregate import demand is the outcome of allocating domestic absorption between
7
domestic goods and aggregate imports, and then aggregate import demand is allocated across
source countries to determine the bilateral trade flows.
There are several sources of protection in the model. The most important involves
bilateral import tariffs. There are also bilateral export subsidies. Domestically, for numerous
countries subsidies are important in agriculture, where they apply to intermediate goods, outputs,
and payments to capital and land.
Three closure rules are used. First, government fiscal balances are fixed in any given
year.4 The fiscal objective is met by changing the level of lump sum taxes on households. This
implies that losses of tariff revenues are replaced by higher direct taxes on households. Second,
the current account balance is fixed. Given that other external financial flows are fixed, this
implies that ex ante changes to the trade balance are reflected in ex post changes to the real
exchange rate. For example, if import tariffs are reduced, the propensity to import increases and
additional imports are financed by increasing export revenues. The latter typically is achieved by
a real exchange rate depreciation. Finally, investment is driven by savings. With fixed public and
foreign saving, investment comes from changes in the savings behavior of households and from
changes in the unit cost of investment. The latter can play an important role in a dynamic model
if imported capital goods are taxed. Because the capital account is exogenous, rates of return
across countries can differ over time and across simulations. The model only solves for relative
prices, with the numéraire, or price anchor, being the export price index of manufactured exports
4 For the sake of simplicity they are fixed in US$ terms at their base year level, minimizing potential
sustainability problems; but this implies they decrease over time as a percentage of GDP for expanding
economies.
8
from high-income countries. This price is fixed at unity in the base year and throughout the
projection period to 2015.
The version of the LINKAGE model used for this study is based on the GTAP database and
is solved with 27 regions and 25 sectors. There is a heavy emphasis on agriculture and food,
comprising 13 of the 25 sectors, and a focus on the largest commodity exporters and importers.
Effects of current protection policies
The LINKAGE model provides a baseline projection of the world economy first to 2005
and then to 2015 assuming no other policy changes. Deviations from that baseline in 2015, due
to total liberalization from 2005, are then examined. The first step requires a pre-simulation to
bring the world as depicted in the GTAP dataset in 2001 up to the start of 2005. In terms of
policy shocks, we include only key multilateral commitments in that pre-simulation, namely the
final stages of Uruguay Round implementation including the phase-out of the Multifibre
Arrangement (MFA), the accession of China and Taiwan to the WTO, and the eastern
enlargement of the European Union from 15 to 25 members. The impacts of those three reforms
are non-trivial: had they not been implemented, the dynamic gains in 2015 from freeing global
merchandise trade would have been an extra $64 billion per year. Nearly half of that difference is
due to the removal of MFA quotas and hence should be considered part of the Uruguay Round's
legacy. The effect of those reforms on tariffs can be seen by comparing the estimates at the start
of 2005 in Table 2 with those for 2001 in Table 1.
The next step is to measure the prospective effects of removing all agricultural subsidies
plus those tariffs summarized in Table 2 over the 2005-2010 period. This could be done for each
9
economy in turn, so as to assess the impact of own-country policies as in Jensen, Robinson and
Tarp (2002). But since each country's policies are there to some extent because of other
countries' policies, and are more likely to be reformed if other regions were to do so at the same
time (as following a multilateral trade negotiation such as the Doha Agenda), a perhaps more-
appropriate question is how each region's welfare, agricultural markets and farm incomes would
change if all trade distortions were to be removed together. Our LINKAGE model's answer to that
question is that it would lead to global gains by 2015 of $287 billion per year. The distribution
across regions of that economic welfare (or equivalent variation in income) gain, reported in
Table 3, suggests two-thirds would accrue to high-income countries. However, as a share of
national income, developing countries would gain more, with an average increase of 0.8 percent
compared with 0.6 percent for high-income countries. The results vary widely across developing
countries, ranging from little impact in the case of Bangladesh and Mexico to 4 or 5 percent
increases in parts of East Asia.
The second column of numbers in Table 3 shows the amount of that welfare gain due to
changes in the international terms of trade for each country. For developing countries as a group
the terms of trade effect is negative, reducing somewhat the gains from improved efficiency of
domestic resource use (especially in China and India). When the terms of trade effect is netted
out, it generates the numbers in parentheses in the final column of Table 3 which can be
interpreted as an indication of the relative degree of inter-sectoral distortion in each economy. By
that indicator, developing countries are more than twice as wasteful of their resources as are
high-income countries ­ and low-income countries are nearly three times as wasteful.
There are several ways to decompose the real income gains from full global trade reform
so as to better understand the sources of the waste for each region. One way is to assess the
10
impacts of developing country liberalization versus industrial country liberalization in different
economic sectors; another is to decompose by policy instrument. The latter gives results very
similar to those reported in Hertel and Keeney (2005), who estimate that market access barriers
explain 93 percent of the welfare effects of agricultural policies, with domestic support and
export subsidy removal contributing only 5 and 2 percentage points, respectively.5
Our results when decomposed by sector are provided in Table 4. They suggest global
liberalization of agriculture and food markets contributes 63 percent of the total global gains
(similar to Hertel and Keeney's 66 per cent). This is consistent with the high tariffs in agriculture
and food versus other sectors shown in Table 1, but is nonetheless remarkable given the low
shares of agriculture in global GDP (4 percent) and global merchandise trade (9 percent). Seven-
tenths of those gains are accounted for by the farm policies of high-income countries, and those
policies also account for the majority of the overall gains from trade reform to high-income
countries. Notice also that developing country gains from high-income country reform are only
half as large from textiles as from agricultural policies.
The full liberalization results suggest little change in the high-income countries' shares of
global output and exports of processed food, beverages and tobacco. Only for primary
agriculture are the changes noticeable: the export share falls by more than one-quarter, from 53
to 38 percent (including intra-EU trade) ­ but the output share falls by only one-sixth, from 30 to
25 percent (Table 5). For developing countries, their share of global output of food and
agricultural products increases 2 percentage points and their share of global exports of those
goods rises 4 percentage points. In absolute terms, agricultural and food output in high-income
5 Hoekman, Ng and Olarreago (2004) reach a similar conclusion from estimating the effects of halving each of
the three types of agricultural distortions, in their case using partial equilibrium analysis.
11
countries would decline but only by 0.1 percent per year over the projection period to 2015
following a move to free trade in all merchandise, instead of rising by 1.6 percent per year.
The impact of full trade reform on agricultural and food output and trade is shown for
each country/region in Table 6, where it is clear that exports are enhanced much more than
output. As a consequence, the global share of agricultural and food production exported rises,
from 9.5 to 13.2 percent (or from 6.6 to 11.6 percent when intra-EU trade is excluded). The
increase in exports of those goods from developing countries would be a huge $191 billion per
year more. Certainly Latin America accounts for a large part of that increase, but all regions'
exports expand and even low-income countries would sell an extra $36 billion worth of such
goods per year (an increase of 52 percent). Also of interest is what happens to food imports:
middle-income countries as a group would see them growing less rapidly than farm exports,
while low-income countries' imports of those goods would grow only as fast as their exports of
food and agricultural products, leaving their food and agricultural self sufficiency ratio
unchanged. Even for high-income countries that ratio would fall only two percentage points,
although it is concentrated in primary agricultural products where the fall is seven points. The
opposite is true in Sub-Saharan Africa and Latin America, while for South Asia and China their
agricultural self sufficiency levels would fall only one percentage point despite their expansion
in exports of labor-intensive manufactures (Table 7).
Would freeing global merchandise trade lead to more trade gain for developing countries
than for high-income countries, given the latter's high protection rates in agriculture and textiles?
This question is pertinent for trade negotiators, who often think more in terms of the boost to the
value of trade than to changes in economic welfare. Table 8 suggests any imbalance of that sort
is not likely to be a major problem, even with complete trade liberalization. Certainly in those
12
two protected sectors exports would increase more for developing than for high-income
countries, but for other manufactures the trade growth for the two regions would have the
opposite bias. Also, much of the developing countries' trade growth is with other developing
countries. Hence for merchandise trade as a whole, developing countries would sell an extra
$318 billion to high-income countries under free trade whereas high-income countries would sell
an extra $290 billion to developing countries. A small amount of services trade liberalization by
developing countries would be sufficient to close that gap, if full reciprocity were sought.
How big would be the consequences of reform for farm output and employment growth
over the implementation period post-2004? Table 9 shows what that annual growth to 2015
would be in the baseline (no policy changes post-2004) and what it would be if all distortions to
merchandise trade were removed. If there were completely free trade, farm output would decline
(instead of growing slightly) in just the EU and Japan while growing slower in a few other highly
protective countries ­ but, for most countries/regions shown in Table 9, farming activities would
expand. This contrasts with the rhetoric suggesting farm protection cuts would cause a major
collapse of protected sectors.
The farm employment picture is somewhat different. Typically, economic growth leads
to declines in not only the relative importance of agriculture (for reasons explained in Anderson
1987 and Martin and Warr 1993) but also in absolute numbers employed in farming once a
country reaches middle-income status. Thus it is not surprising that numerous middle- and high-
income countries are projected to lose farm jobs over the next decade in the baseline scenario of
Table 9. For the most protected farm sectors, that rate of farm employment decline would more
than double if the world were to move to completely free trade. For other economies, though,
13
farm employment would grow a little faster, allowing developing countries to absorb more
workers on their farms.
Such reform also raises the share of agricultural and food production that is exported
globally, from 9.5 percent in the baseline to 13.2 percent under free merchandise trade (Table
10). Even in the protected countries this ratio rises a little, because farm resources would move
within the sector from import-competing to more-competitive farming activities.
The relatively small percentage changes in net national economic welfare hide the fact
that redistributions of welfare among groups within each country following trade reform can be
much larger. This is clear from the impacts on real rewards to labor, capital and land that are
reported in Table 11. The results also strongly support the expectation from trade theory that
returns to unskilled labor rise substantially in developing countries, and by more than wages of
skilled workers, which in turn rise more than earnings from produced capital. That is, full reform
would be likely to improve equity and reduce poverty in developing countries, given that the vast
majority of their poor earn their income as unskilled laborers (including as farmers). For high-
income countries, again consistent with standard trade theory, skilled workers gain more than
unskilled workers. Those European and Northeast Asian farmers renting agricultural land would
benefit from a large fall in farm rental costs, more or less offsetting the fall in prices for their
output, while earnings of landowners in those countries would lose.6
Those changes in factor rewards assume labor is mobile between sectors. In the most
densely populated developing countries full liberalization would encourage more farm workers
to take up now-more-rewarding work in labor-intensive manufacturing and service activities, so
6 Their loss is relative to the no-reform baseline, which ignores the fact that such farm landowners have long
enjoyed protection-inflated returns, in some cases for several decades.
14
value-added in agriculture would fall not only in economies where it has been highly protected
(Europe, Northeast Asia and the US) but also in South Asia ­ whose trade policies have a
slightly pro-agricultural bias according to the GTAP database, and which enjoys expanding
market access abroad for those non-agricultural products in which the region has a strong
comparative advantage.7 All other developing country regions would see a rise in net farm
income though (as would the developed country Cairns Group members of Canada, Australia
and New Zealand). That is true of China not only because it has already reduced much of its
agricultural protection as part of its reforms associated with its accession to WTO at the end of
2001, but also because it faces extremely high tariff barriers in it export markets for farm
products (Jean, Laborde and Martin 2005). And it is true in particular of the Sub-Saharan African
region, even when southern Africa is separated out, despite the fact that there are numerous net
food importing and preference-receiving exporting countries in that region (see Anderson,
Martin and van der Mensbrugghe (2005a) for more details). Table 12 shows separately the
contributions of high-income and developing countries' farm policy reforms to that outcome,
from which it is clear that most of the effect comes from one or other of those reforms, with only
a minor contribution to the residual from non-agricultural sectors. Those value added changes are
due in considerable part to the changes in import and export prices for farm and other products,
which are summarized in Table 13.
Of particular importance to Brazil and some Sub-Saharan African countries is the case of
cotton, which is receiving special attention in the WTO's Doha Development Agenda following
the Cancun Trade Ministerial in 2003 and the Dispute Settlement case that went against the US
7 The move to free trade would boost South Asia's ratio of production to consumption in textiles and clothing
from 1.51 to 1.66, for example.
15
in 2004. Under full trade and subsidy liberalization, global cotton markets would change
dramatically: the value of production would fall by one-third or more than $5 billion per year in
high-income countries (mostly in the US), and the value of their exports would fall by $3.6
billion. The world totals would hardly change though, as developing country output and exports
of cotton would expand by about the same amounts, with Sub-Saharan Africa enjoying more of
that gain than any other region (Table 14). Indeed cotton is so important in Sub-Saharan Africa
minus South Africa that it contributes one-quarter of that region's net gain in agricultural value
added from full liberalization.8
The bottom line, therefore, is that if all current distortions to world trade in merchandise
were phased out over the rest of this decade then, according to the latest GTAP database and the
Linkage model, by 2015 developing country agricultural production, employment and real net
income would be greater than without such reform. And it would be greater in most regions
within the developing country group, the exceptions being South Asia and Eastern Europe where
import tariffs are higher for agricultural than non-agricultural goods. This does not necessarily
mean that if each individual developing country were to unilaterally liberalize we would find
farmers benefiting in all cases except in South Asia and Eastern Europe; but if we were to run
those many individual model simulations we may well get that result also, since, as is apparent
from Table 3, terms of trade effects of reforms by others are usually dominated by efficiency
gains from own reforms except for the least-distorted economies.
8 If full cotton liberalization was included in the Doha package, it would nearly double both the net welfare gain
and the boost in net farm income in the SSA region. Furthermore, the share of all developing countries in global
cotton exports would be 85 percent instead of 56 percent in 2015 ­ all of which vindicates the efforts to ensure
cotton receives specific and substantial attention in the Doha negotiations (see Anderson, Martin and van der
Mensbrugghe 2005b).
16
Finally, which commodities contribute most to the global cost of agricultural protection?
That depends not only on the nominal rate of protection but also on the relative size of each sub-
sector and the different degrees of responsiveness of inputs to changes in relative output prices.
According to the Linkage model, rice, sugar and meat are the key contributors (Table 15).9 The
first two of those especially are of importance to developing country farmers, so it is not
surprising that their interest in agricultural trade reform is so intense.
Lessons, implications and areas for further research
The following are the key messages that emerge from our analysis:
ˇ The potential gains from global trade reform are large, including for developing countries
and especially when they participate in the reform, despite its adverse terms of trade
impact on many developing countries;
ˇ Agriculture is where the greatest gains from liberalization would occur;
ˇ Liberalization would cause farm output and farm employment to be greater in developing
countries relative to the baseline, except in South Asia;
ˇ It is the poorest people that appear to be most likely to gain from global trade
liberalization, namely farmers and unskilled laborers in developing countries; and, in
particular,
9 Dairy's estimated contribution is much less despite the high rates of assistance to dairy farmers, presumably
because the GTAP protection database relies just on tariffs and excludes the protective effect of non-tariff
import barriers such as sanitary and phytosanitary restrictions, which may be much higher for fluid milk than
for most other farm products.
17
ˇ Net farm income would be enhanced in all developing country regions other than South
Asia (where job growth would be greater in non-farm activities).
To realize that potential gain, it is in agriculture that by far the largest cuts in bound
tariffs and subsidies are required. The political sensitivity of farm support programs, coupled
with the complexities of the measures introduced in the Uruguay Round Agreement on
Agriculture and of the modalities set out in the Doha Framework Agreement of July 2004, make
that a daunting task. However, with global gains of the order of $290 billion per year at stake
from removing trade barriers, even if no reforms were forthcoming in services, and even if the
counterfactual is the status quo rather than protectionist backsliding, the political will needs to be
found to bring about such reform. The WTO's Doha Development Agenda is an obvious vehicle
for moving down this path (Anderson and Martin 2005a, b). Multilateral cuts in tariff bindings
are especially helpful because they can lock in previous unilateral trade liberalizations that
otherwise would remain unbound and hence vulnerable to reversals to higher protection; and
they can be used as an opportunity to multilateralize previously agreed preferential trade
agreements and thereby reduce the risk of trade diversion from those bilateral or regional
arrangements. It remains to be seen whether the political will can be mustered to bring that Doha
round to a successful conclusion.
The results concerning the extent of bias in trade policies against or in favor of
agriculture are very much dependent on the levels of distortion in the GTAP database of course.
Those for high-income countries are reasonably reliable, thanks in large part to the protection
estimates provided by the OECD (2005 and earlier). Currently available estimates of
(particularly agricultural) trade distortions and subsidies in developing countries are less reliable.
Nor are many estimates provided in the GTAP database of export taxes or tax equivalents of
18
quantitative restrictions and bans on exports. A new project at the World Bank is seeking to
provide better estimates of that sort. Distortions to factor markets, particularly labor, may also
have an important influence on the results for some countries if they were to be included in the
model. More-challenging tasks would be to also provide estimates of distortions to services trade
and foreign direct investment, so as to see what impact they also have on agricultural and other
goods production and trade; and to estimate the poverty consequences of such reforms (building
on pioneering empirical work in Hertel and Winters 2005).
19
References
Anderson, K. (1987), `On Why Agriculture Declines With Economic Growth', Agricultural
Economics 1(3): 195-207, June.
Anderson, K. and W. Martin (eds.) (2005a), Agricultural Trade Reform and the Doha
Development Agenda, New York: Palgrave Macmillan, co-published with the World
Bank (forthcoming).
Anderson, K. and W. Martin (2005b), `Agricultural Trade Reform and the Doha Development
Agenda', The World Economy 28(9), September (forthcoming).
Anderson, K., W. Martin and D. van der Mensbrugghe (2005a), `Would Multilateral Trade
Reform Benefit Sub-Saharan Africa?" Policy Research Working Paper No. 3616, World
Bank, Washington DC, June.
Anderson, K., W. Martin and D. van der Mensbrugghe (2005b), `Doha Merchandise Trade
Reform: What's at Stake for Developing Countries?' Policy Research Working Paper No.
xxxx, World Bank, Washington DC, August (forthcoming).
Bautista, R.M., S. Robinson, P.Wobst and F. Tarp (2001), `Policy Bias and Agriculture: Partial
and General Equilibrium Measures', Review of Development Economics 5(1): 89-104,
February.
Bouët, A., Y. Decreux, L. Fontagné, S. Jean and D. Laborde (2004), `A Consistent, ad valorem
Equivalent Measure of Applied Protection Across the World: The MAcMap-HS6
Database', mimeo, CEPII, Paris, 20 December.
Crawford, J.-A. and R.V. Fiorentino (2005), `The Changing landscape of Regional Trade
Agreements', Discussion paper No. 8, Geneva: World Trade Organization.
20
Drabek, Z. and M. Bacchetta (2004), `Tracing the Effects of WTO Accession on Policy-making
in Sovereign States: Preliminary Lessons from the Recent Experience of Transition
Countries', The World Economy 27: 1083-1125.
Jean, S., D. Laborde and W. Martin (2005), `Consequences of Alternative Formulas for
Agricultural Tariff Cuts', Ch 4 in Agricultural Trade Reform and the Doha Development
Agenda, edited by K. Anderson and W. Martin, New York: Palgrave Macmillan
(forthcoming).
Hertel, T. (ed.) (1997), Global Trade Analysis: Modeling and Applications, Cambridge and New
York: Cambridge University Press.
Hertel, T.W. and R. Keeney (2005), `What's at Stake: The Relative Importance of Import
Barriers, Export Subsidies and Domestic Support', Ch. 2 in Agricultural Trade Reform
and the Doha Development Agenda edited by K. Anderson and W. Martin, New York:
Palgrave Macmillan (forthcoming).
Hertel, T.W. and L.A. Winters (eds.) (2005), Putting Development Back Into the Doha Agenda:
Poverty Impacts of a WTO Agreement, New York: Palgrave Macmillan, co-published
with the World Bank (forthcoming).
Hoekman, B., F. Ng and M. Olarreaga (2004), `Agricultural Tariffs versus Subsidies: What's
More Important for Developing Countries?' World Bank Economic Review 18(2): 175-
204.
Jensen, H.T., S. Robinson and F. Tarp (2002), `General Equilibrium Measures of Agricultural
Policy Bias in Fifteen Developing Countries', TMD Discussion Paper No. 105, IFPRI,
Washington DC, October.
21
Krueger, A.O., M. Schiff and A. Valdes (1988), 'Agricultural Incentives in Developing
Countries: Measuring the Effect of Sectoral and Economy-wide Policies', World Bank
Economic Review 2(3): 255-72, September.
Legg, W. (2003), `Agricultural Subsidies: Measurement and Use in Policy Evaluation', Journal
of Agricultural Economics 54(2): 175-200, July.
Martin, W. and P.G. Warr (1993), `Explaining the Relative Decline of Agriculture: A Supply-
Side Analysis for Indonesia', World Bank Economic Review 7(3): 381-401, September.
OECD (2005), Agricultural Policies in OECD Countries: Monitoring and Evaluation 2005,
Paris: Organization for Economic Cooperation and Development.
Piermartini, R. (2004), `The Role of Export Taxes in the Field of Primary Commodities', WTO
Discussion Paper No. 4, Geneva.
Thiele, R. (2004), `The Bias Against Agriculture in Sub-Saharan Africa: Has it Survived 20
Years of Structural Adjustment Programs?' Quarterly Journal of International
Agriculture 42(1): 5-20.
Tyers, R. and K. Anderson (1992), Disarray in World Food Markets: A Quantitative
Assessment, Cambridge and New York: Cambridge University Press.
van der Mensbrugghe, D. (2004), `LINKAGE Technical Reference Document: Version 6.0',
mimeo, The World Bank, Washington, DC. Accessable at
http://siteresources.worldbank.org/INTPROSPECTS/Resources/334934-
1100792545130/LinkageTechNote.pdf
World Bank (2002), Global Economic Prospects and the Developing Countries 2002: Making
Trade Work for the Poor, Washington DC: The World Bank.
22
World Bank (2004), Global Economic Prospects: Realizing the Development Promise of the
Doha Agenda, Washington DC: The World Bank.
World Bank (2005), Global Economic Prospects: Trade, Regionalism, and Development,
Washington DC: The World Bank.
23
Table 1: Import-weighted average applied tariffs, by sector and region, 2001
(percent)
Agriculture Other
and primary Textiles Other
processed productsa and manufact- ALL
Importing region: food clothing uring GOODS
High-income countriesb 16.0 1.0 7.5 1.3 2.9
Developing countries 17.7 6.5 17.0 8.3 9.9
Middle-income countries 16.5 4.6 16.8 7.3 8.9
Low-income countries 22.2 14.2 17.9 14.5 15.9
East Asia and Pacific 26.3 17.8 8.6 10.5
South Asia 33.9 20.1 22.2 23.5
Europe & Central Asia 14.8 10.7 4.1 6.0
Middle East & N. Africa 14.1 27.1 7.2 9.8
Sub-Saharan Africa 18.2 23.7 10.5 12.6
Latin America & Carib. 10.3 5.1 11.3 7.1 7.7
World total 16.7 10.2 3.5 5.2
aForestry, fishing, fuels, minerals and non-ferrous metals.
bIntra-EU15 trade is ignored in calculating weights for determining tariff averages.
Source: Authors' compilations from the GTAP database Version 6.05
24
Table 2: Import-weighted average applied tariffs, by sector and country, 2005
(percent)
Agriculture (Primary (Processed Textiles Other
and processed agriculture food only) and manufac-
Importing region: food only) clothing turing
World 15.2 9.3 3.1
High-income 15.9 7.3 1.2
Australia & NZ 2.6 0.3 3.3 13.9 4.1
EU25 + EFTA 13.9 13.2 14.7 5.1 1.7
United States 2.4 2.3 2.5 9.6 0.9
Canada 9.0 1.2 14.1 8.7 0.5
Japan 29.3 48.0 20.8 9.0 0.4
S. Korea & Taiwan 53.0 84.5 22.4 9.2 3.6
Hong Kong & Sing. 0.1 0.0 0.2 0.0 0.0
Developing countriesb 14.2 14.3 7.1
Middle-income 12.1 13.6 6.0
Argentina 7.1 5.6 7.8 11.1 10.1
Brazil 5.0 2.4 9.0 14.7 9.7
China 10.3 9.9 11.0 9.6 5.5
Mexico 10.3 10.8 9.7 7.8 4.3
Russia 13.5 14.6 12.8 15.8 7.8
South Africa 8.6 5.9 10.6 21.9 5.4
Thailand 16.7 12.7 19.2 16.4 7.6
Turkey 16.6 16.4 17.0 3.8 1.2
Rest of East Asia 13.4 18.6 9.0 8.7 3.5
Rest of LAC 10.8 9.2 11.8 12.9 8.4
Rest of ECA 15.7 10.4 19.5 9.3 3.2
M. East &N. Africa 13.1 8.2 18.3 23.9 7.2
Low-income 22.0 17.9 14.1
Bangladesh 12.7 7.4 21.2 29.9 16.2
India 49.9 25.7 75.6 26.5 24.2
Indonesia 5.0 4.3 6.2 8.0 4.3
Vietnam 37.1 13.1 44.8 29.1 12.3
Rest of South Asia 21.1 14.2 32.0 6.6 14.3
Selected SSAfricaa 11.8 10.2 13.0 12.5 7.5
Rest of SSAfrica 21.2 18.0 23.6 26.2 14.0
Rest of the World 11.8 1.9 18.7 5.6 8.9
aThe Selected Sub-Saharan African countries (for which national modules are available
in the LINKAGE Model) include Botswana, Madagascar, Malawi, Mozambique, Tanzania,
Uganda, Zambia, Zimbabwe.
bNumbers in parentheses are the averages at the start of 2005 following WTO accession
by China and end of MFA.
Source: Authors' projections from the GTAP database Version 6.05 using the World
Bank's LINKAGE model
25
Table 3: Impacts on real income from full liberalization of global merchandise
trade, by country/region, 2015
(relative to the baseline, in 2001 dollars and percent)
Gain due to
improved
Change in efficiency of
Total real income due just resource use net Total real gain
income gain to change in of terms of trade as percentage
p.a. terms of trade effect of baseline
($billion) ($billion) ($billion) income in 2015a
Australia and New Zealand 6.1 3.5 2.6 1.0 (0.4)
EU 25 plus EFTA 65.2 0.5 64.7 0.6 (0.6)
United States 16.2 10.7 6.5 0.1 (0.0)
Canada 3.8 -0.3 4.1 0.4 (0.4)
Japan 54.6 7.5 47.1 1.1 (1.0)
Korea and Taiwan 44.6 0.4 44.2 3.5 (3.5)
Hong Kong and Singapore 11.2 7.9 3.3 2.6 (0.8)
Argentina 4.9 1.2 3.7 1.2 (0.9)
Bangladesh 0.1 -1.1 1.2 0.2 (2.4)
Brazil 9.9 4.6 5.3 1.5 (0.8)
China 5.6 -8.3 13.9 0.2 (0.5)
India 3.4 -9.4 12.8 0.4 (1.5)
Indonesia 1.9 0.2 1.7 0.7 (0.7)
Thailand 7.7 0.7 7.0 3.8 (3.4)
Vietnam 3.0 -0.2 3.2 5.2 (5.5)
Russia 2.7 -2.7 5.4 0.6 (1.2)
Mexico 3.6 -3.6 7.2 0.4 (0.8)
South Africa 1.3 0.0 1.3 0.9 (0.9)
Turkey 3.3 0.2 3.1 1.3 (1.2)
Rest of South Asia 1.0 -0.8 1.8 0.5 (0.9)
Rest of East Asia 5.3 -0.9 6.2 1.9 (2.2)
Rest of LAC 10.3 0.0 10.3 1.2 (1.2)
Rest of ECA 1.0 -1.6 2.6 0.3 (0.8)
Middle East and North Africa 14.0 -6.4 20.4 1.2 (1.7)
Selected SSA countries 1.0 0.5 0.5 1.5 (0.8)
Rest of Sub-Saharan Africa 2.5 -2.3 4.8 1.1 (2.2)
Rest of the World 3.4 0.1 3.3 1.5 (1.5)
High-income countries 201.6 30.3 171.3 0.6 (0.5)
Developing countries 85.7 -29.7 115.4 0.8 (1.1)
Middle-income countries 69.5 -16.7 86.2 0.8 (1.0)
Low-income countries 16.2 -12.9 29.1 0.8 (1.4)
East Asia and Pacific 23.5 -8.5 32.0 0.7 (1.0)
South Asia 4.5 -11.2 15.7 0.4 (1.4)
Europe and Central Asia 7.0 -4.0 11.0 0.7 (1.1)
Sub-Saharan Africa 4.8 -1.8 6.6 1.1 (1.5)
Latin America and the Carib 28.7 2.2 26.5 1.0 (0.9)
World total 287.3 0.6 286.7 0.7 (0.7)
aNumbers in parentheses refer to that due to efficiency gains net of terms of trade effects.
Source: Authors' World Bank LINKAGE model simulations
26
Table 4: Regional and sectoral source of gains from full liberalization of global
merchandise trade, developing and high-income countries, 2015
(relative to the baseline scenario)
Gains by region in $billion Percent of regional gain
Devel- High- Devel- High-
oping income World oping income World
Developing countries liberalize:
Agriculture and food 28 19 47 33 9 17
Textiles and clothing 9 14 23 10 7 8
Other merchandise 6 52 58 7 26 20
All sectors 43 85 128 50 42 45
High-income countries liberalize:
Agriculture and food 26 109 135 30 54 47
Textiles and clothing 13 2 15 15 1 5
Other merchandise 4 5 9 5 3 3
All sectors 43 116 159 50 58 55
All countries liberalize:
Agriculture and food 54 128 182 63 63 63
Textiles and clothing 22 16 38 25 8 14
Other merchandise 10 57 67 12 29 23
All sectors 86 201 287 100 100 100
aSmall interaction effects are distributed proportionately and numbers are rounded to
sum to 100 percent
Source: Authors' World Bank LINKAGE model simulations
27
Table 5: Developing countries' shares of global output and exports, by sector, 2015
(percent)
Primary Processed food, Textiles and Other
agriculture beverages and clothing manufacturing
tobacco
Output
-- baseline 70 40 62 35
-- free trade 75 40 65 35
Exportsa
-- baseline 47 34 63 30
-- free trade 62 40 67 32
aIncluding intra-EU trade
Source: Authors' World Bank LINKAGE model simulations
28
Table 6: Impacts of full global trade liberalization on agricultural and food output
and trade, by country/region, 2015
(relative to baseline)
$billion Percent change relative to
baseline
Exports Imports Output Exports Imports Output
Australia and New Zealand 18.0 1.4 27.9 38.0 23.0 20.5
EU 25 plus EFTA 21.7 103.5 -185.8 -10.8 39.3 -12.3
United States 18.4 16.5 30.7 11.6 25.6 0.0
Canada 14.6 6.9 7.2 40.2 54.3 4.8
Japan 2.8 34.7 -91.7 60.4 169.7 -18.4
Korea and Taiwan 33.2 12.3 -0.4 600.2 189.8 20.2
Hong Kong and Singapore 7.0 1.5 7.4 115.2 7.6 35.4
Argentina 10.4 0.7 12.2 44.2 36.9 11.5
Bangladesh 0.8 0.4 -2.5 60.9 15.6 0.8
Brazil 38.0 2.8 66.4 120.6 48.4 34.0
China 15.1 24.1 -9.9 145.6 27.3 -0.9
India 5.1 13.4 -23.8 53.2 165.4 -3.7
Indonesia 3.6 1.9 4.5 32.2 23.5 2.4
Thailand 5.6 5.2 5.3 29.2 57.2 4.7
Vietnam 1.2 3.3 -2.1 13.9 170.4 -13.3
Russia 0.7 4.4 -7.8 15.4 22.3 -5.4
Mexico 11.9 6.7 6.2 66.0 52.9 2.2
South Africa 2.4 1.1 1.4 55.9 40.2 4.9
Turkey 4.3 4.3 -0.1 109.4 140.3 0.5
Rest of South Asia 2.9 3.7 -1.5 57.1 83.3 -1.8
Rest of East Asia 9.4 5.8 7.4 61.7 50.7 6.8
Rest of LAC 36.0 9.6 37.0 68.1 42.3 11.7
Rest of ECA 9.2 10.9 -22.2 106.0 90.5 -1.6
Middle East and North Africa 13.2 17.5 -7.8 64.1 43.1 -1.2
Selected SSA countries 4.5 1.3 5.3 50.0 74.4 9.2
Rest of Sub Saharan Africa 9.5 8.1 -4.1 45.4 79.2 -0.6
Rest of the World 8.2 5.8 2.9 168.3 123.3 4.4
High-income countries 115.8 176.7 -204.7 15.7 65.5 -5.3
Developing countries 191.9 131.0 66.8 67.4 51.5 2.2
Middle-income countries 156.1 93.1 88.2 72.7 41.9 3.2
Low-income countries 35.8 37.9 -21.4 52.3 99.3 -1.0
East Asia and Pacific 34.8 40.4 5.2 54.4 35.5 0.1
South Asia 8.9 17.5 -27.8 55.1 122.9 -3.0
Europe and Central Asia 14.2 19.6 -30.0 79.7 62.6 -1.9
Sub Saharan Africa 16.4 10.5 2.6 47.7 71.6 2.1
Latin America and the Caribbean 96.3 19.8 121.8 75.7 46.1 13.8
World total (excluding intra-European trade) 307.7 307.7 -137.8 36.3 59.8 -1.3
Source: Authors' World Bank LINKAGE model simulations
29
Table 7: Impact of global liberalization on self sufficiencya in agricultural and other products, selected regions, 2015
High-income Developing Sub-Sahahan Latin America South
countries countries Africa & Caribbean Asia China
Global Global Global Global Global Global
Baseline lib'n Baseline lib'n Baseline lib'n Baseline lib'n Baseline lib'n Baseline lib'n
Rice 101 78 100 103 92 82 99 99 102 103 100 108
Wheat 160 140 91 94 55 39 92 127 99 98 92 93
Other grains 119 134 93 88 101 102 107 109 99 99 89 42
Oil seeds 135 79 90 106 158 278 188 249 100 102 3 3
Sugar 97 66 102 115 110 120 126 173 100 100 56 35
Plant-based fibers 121 84 96 103 389 698 95 107 89 92 94 96
Vegetables and fruits 89 80 103 105 139 144 147 185 97 91 98 98
Other crops 86 87 112 111 168 176 142 134 105 106 19 17
Livestock 104 104 98 98 103 103 103 102 99 99 96 95
Other natural resources 94 94 104 104 126 127 129 129 97 97 93 93
Fossil fuels 81 80 124 125 152 160 119 118 71 61 88 85
Processed meats 101 93 99 111 97 139 105 134 108 117 91 88
Vegetable oils and fats 98 91 102 108 89 76 113 107 77 34 96 91
Dairy products 104 103 90 94 78 79 95 96 97 98 66 61
Other food, beverages & tob. 98 101 102 99 102 96 108 108 112 110 99 98
Textiles 97 98 102 101 81 68 89 83 132 137 102 101
Wearing apparel 68 61 162 176 89 73 95 84 527 792 228 260
Leather products 60 56 139 144 92 66 110 92 173 191 158 167
Chemicals rubber & plastics 105 106 92 91 75 71 82 77 95 94 94 91
Iron and steel 101 101 99 98 106 107 102 95 98 95 94 93
Motor vehicles and parts 103 104 91 87 66 76 105 105 97 89 92 82
Capital goods 103 103 95 95 48 47 86 83 82 82 105 106
Other manufacturing 96 97 107 106 121 116 100 95 101 98 112 113
Agriculture and food 100 98 100 102 109 113 112 122 100 98 95 94
Agriculture 101 94 100 102 119 125 122 136 100 99 94 93
Processed foods 99 99 101 101 100 100 106 113 103 95 97 96
Textile and wearing apparel 79 76 118 121 84 69 95 85 151 166 128 132
Other manufacturing 99 100 101 100 98 98 96 92 92 89 102 102
aSelf sufficiency is defined as domestic production as a percentage of domestic consumption measured in value terms at fob prices.
Source: Authors' World Bank LINKAGE model simulations
Table 8: Changes in bilateral trade flows from full global liberalization , 2015
a
(Difference in bilateral trade flows at FOB prices in 2015 compared to the baseline, $billion)
Importer:
High-
income Developing
World countries countries
Exporter: Agriculture and food
World 314 186 128
High-income 104 54 50
Developing 210 133 77
Textiles and clothing
World 164 79 85
High-income 47 8 40
Developing 117 71 46
Other manufacturing
World 595 227 368
High-income 312 112 200
Developing 284 114 168
All merchandise trade
World 1073 492 581
High-income 463 174 290
Developing 610 318 291
a Aggregations exclude intra-EU trade
Source: Authors' World Bank LINKAGE model simulations
Table 9: Agricultural output and employment growth, baseline and full liberalization,
2005-2015
(annual percent growth rate between 2005 and 2015)
Output growth Employment growth
Full global Full global
Baseline liberaliz'n Baseline liberaliz'n
Australia & New Zealand 3.5 5.2 0.4 1.9
EU 25 plus EFTA 1.0 -1.5 -1.8 -3.9
United States 2.2 1.3 -0.8 -2.1
Canada 3.5 5.2 0.2 1.9
Japan 0.5 -4.3 -2.7 -6.5
Korea and Taiwan 2.2 0.1 -1.3 -3.9
Hong Kong and Singapore 2.8 3.3 0.0 0.2
Argentina 2.9 5.1 0.9 3.3
Bangladesh 4.2 4.4 1.1 1.2
Brazil 3.3 6.1 1.1 4.0
China 4.3 4.3 0.8 0.7
India 4.3 4.1 1.0 0.6
Indonesia 3.0 2.9 -0.7 -0.7
Thailand -0.1 1.3 -4.6 -3.7
Vietnam 5.8 6.1 3.9 3.5
Russia 1.5 1.0 -2.3 -2.7
Mexico 3.9 4.1 2.0 2.3
South Africa 2.5 3.3 0.0 0.8
Turkey 3.0 2.6 -0.5 -1.2
Rest of South Asia 4.8 4.8 2.0 1.9
Rest of East Asia 3.7 3.5 0.2 -0.1
Rest of LAC 4.4 6.6 1.9 3.8
Rest of ECA 3.3 3.3 0.0 -0.1
Middle East & N. Africa 4.0 4.0 1.5 1.4
Selected SSA countries 5.3 5.7 3.0 3.3
Rest of Sub-Saharan Africa 4.6 4.8 2.2 2.5
Rest of the World 5.0 6.4 2.4 3.5
High-income countries 1.6 -0.1 -1.5 -3.1
Developing countries (WB) 3.9 4.2 1.0 1.2
Middle-income countries 3.7 4.1 0.4 0.3
Low-income countries 4.4 4.5 1.2 0.9
East Asia and Pacific 4.0 4.0 -0.5 -0.8
South Asia 4.4 4.2 1.5 1.4
Europe and Central Asia 3.0 2.9 2.3 2.6
Middle East and N. Africa 4.0 4.0 1.7 3.4
Sub-Saharan Africa 4.5 4.9 0.2 0.0
Latin America and Carib. 3.8 5.8 0.4 1.9
World total 3.2 2.9 -1.8 -3.9
Source: Authors' World Bank LINKAGE model simulations
32
Table 10: Share of agricultural and food production exported, 2001 and 2015
(percent)
Full global
Baseline Baseline liberaliz'n
2001 2015
Australia & New Zealand 33.3 37.2 42.7
EU 25 plus EFTA 16.7 17.3 17.6
EU 25 plus EFTA (excl. intra-EU25) 4.0 5.1 7.7
United States 6.3 7.9 9.2
Canada 24.5 29.5 40.0
Japan 0.9 1.2 2.3
Korea and Taiwan 4.4 4.8 26.5
Hong Kong and Singapore 26.0 30.0 47.8
Argentina 21.6 25.2 32.5
Bangladesh 1.7 3.6 5.7
Brazil 15.3 17.3 28.9
China 3.3 0.9 2.2
India 3.5 3.0 4.7
Indonesia 11.9 10.0 12.9
Thailand 30.2 28.2 34.6
Vietnam 23.9 26.9 35.3
Russia 6.1 5.5 6.7
Mexico 5.6 7.8 13.2
South Africa 16.0 12.7 18.8
Turkey 9.6 6.0 12.4
Rest of South Asia 6.0 6.2 9.9
Rest of East Asia 16.1 14.6 22.1
Rest of LAC 13.9 18.1 27.1
Rest of ECA 2.4 1.7 3.7
Middle East & N. Africa 5.2 6.7 11.2
Selected SSA countries 13.2 18.1 25.4
Rest of Sub-Saharan Africa 11.2 15.8 23.3
Rest of the World 6.6 7.0 17.7
High-income countries 5.8 7.5 11.6
Developing countries 7.5 6.9 11.6
Middle-income countries 7.6 6.6 11.4
Low-income countries 7.3 7.9 12.4
East Asia and Pacific 7.2 4.1 6.5
South Asia 3.8 3.6 5.7
Europe and Central Asia 3.7 2.7 5.0
Sub-Saharan Africa 12.5 15.8 23.1
Latin America & the Caribbean 12.7 15.9 24.8
World total 9.5 9.5 13.2
World total (excl. intra-EU25) 6.6 7.2 11.6
Source: Authors' World Bank LINKAGE model simulations
33
Table 11: Impacts of full global merchandise trade liberalization on real factor prices,
2015a
(relative to the baseline in 2015, percent)
Un-
skilled Skilled Capitalb Landb
wages wages user cost user cost CPI
Australia and New Zealand 3.1 1.1 -0.3 17.4 1.2
EU 25 plus EFTA 0.0 1.3 0.7 -45.4 -1.3
United States 0.1 0.3 0.0 -11.0 -0.4
Canada 0.7 0.7 0.4 22.8 -0.9
Japan 1.3 2.2 1.1 -67.4 -0.1
Korea and Taiwan 6.5 7.1 3.8 -45.0 -0.7
Hong Kong and Singapore 3.2 1.6 0.3 4.4 1.1
Argentina 2.9 0.5 -0.7 21.3 0.3
Bangladesh 1.8 1.7 -0.2 1.8 -7.2
Brazil 2.7 1.4 1.6 32.4 2.2
China 2.2 2.2 2.8 -0.9 -0.4
India 2.8 4.6 1.8 -2.6 -6.0
Indonesia 3.3 1.5 0.9 1.0 0.5
Thailand 13.2 6.7 4.2 11.4 -0.6
Vietnam 25.3 17.6 11.0 6.8 -2.3
Russia 2.0 2.8 3.5 -2.2 -3.3
Mexico 2.0 1.6 0.5 2.8 -1.4
South Africa 2.8 2.5 1.8 5.7 -1.6
Turkey 1.3 3.4 1.1 -8.1 -0.3
Rest of South Asia 3.7 3.2 0.1 0.1 -2.7
Rest of East Asia 5.8 4.2 5.2 -0.9 -1.6
Rest of LAC 5.7 1.4 -0.4 17.8 -1.2
Rest of ECA 2.3 4.2 2.1 -0.3 -2.6
Middle East and North Africa 4.1 4.1 2.6 2.4 -3.1
Selected SSA countries 6.0 1.6 0.0 4.6 0.4
Rest of Sub-Saharan Africa 8.2 6.5 2.2 5.2 -5.0
Rest of the World 4.4 2.7 1.1 6.3 -1.4
High-income countries 0.6 1.1 0.5 -20.0 -0.6
Developing countries 3.5 3.0 1.9 0.9 -1.7
Middle-income countries 3.2 2.6 1.9 2.2 -1.1
Low-income countries 4.2 3.9 1.9 -1.0 -4.0
World total 1.2 1.5 0.8 -0.8 -0.8
aNominal factor prices deflated by the consumer price index (CPI).
bThe user cost of capital and land represents the subsidy inclusive rental cost.
Source: Authors' World Bank LINKAGE model simulations
34
Table 12: Effects of full liberalization of global agricultural and other merchandise trade
on agricultural value added, by country/region, 2015
(relative to baseline, billion US dollars and percent)
$billion percent
High- High-
Developing income Developing income
country country All goods country country All goods
agr & food agr&food trade agr & food agr &food trade
policies policies policies policies policies policies
Australia and New Zealand 2.5 3.2 6.4 10.1 13.0 25.6
EU 25 plus EFTA 7.3 -42.0 -39.1 4.9 -28.3 -26.4
United States 5.1 -20.7 -18.2 4.2 -17.0 -15.0
Canada 2.0 1.4 3.4 13.3 9.6 23.3
Japan 0.2 -17.7 -17.7 0.4 -39.6 -39.5
Korea and Taiwan 0.5 -10.1 -9.5 1.7 -35.4 -33.3
Hong Kong and Singapore 0.1 0.1 0.1 3.6 5.0 7.5
Argentina 0.4 4.9 6.1 2.1 27.4 33.8
Bangladesh -0.4 0.2 -0.5 -3.3 1.7 -4.4
Brazil 0.0 15.1 15.1 0.1 46.2 46.3
China -16.3 13.3 0.3 -3.8 3.1 0.1
India -17.3 2.9 -17.1 -8.2 1.4 -8.1
Indonesia -0.1 1.0 0.8 -0.4 3.3 2.7
Thailand 1.1 3.1 3.8 7.2 20.4 25.0
Vietnam 0.9 0.3 0.8 14.5 5.7 13.6
Russia -1.8 0.7 -1.4 -8.4 3.2 -6.5
Mexico -3.8 7.9 0.9 -9.9 20.9 2.5
South Africa 0.1 0.4 0.5 1.3 7.8 9.6
Turkey -2.9 0.9 -2.0 -10.3 3.0 -7.2
Rest of South Asia -1.7 1.2 -0.6 -3.7 2.7 -1.3
Rest of East Asia -1.4 1.2 -0.2 -5.5 4.6 -0.7
Rest of LAC 1.9 19.7 22.9 2.5 26.0 30.2
Rest of ECA -2.1 1.4 -1.1 -3.3 2.3 -1.8
Middle East and North Africa -4.8 6.2 0.3 -4.4 5.6 0.3
Selected SSA countries 0.4 1.1 1.5 2.7 6.5 9.1
Rest of Sub Saharan Africa -0.7 3.0 2.3 -1.7 7.2 5.4
Rest of the World 0.7 2.5 3.1 3.4 13.2 16.4
High-income countries 17.6 -85.8 -74.6 4.6 -22.3 -19.4
Developing countries -47.9 87.1 35.6 -3.9 7.0 2.9
Middle-income countries -29.6 74.8 45.3 -3.4 8.7 5.3
Low-income countries -18.2 12.3 -9.7 -4.8 3.2 -2.5
East Asia and Pacific -15.8 18.9 5.5 -3.2 3.8 1.1
South Asia -19.4 4.4 -18.1 -7.2 1.6 -6.8
Europe and Central Asia -6.8 3.0 -4.5 -6.0 2.6 -4.0
Middle East and North Africa -4.8 6.2 0.3 -4.4 5.6 0.3
Sub Saharan Africa -0.2 4.5 4.3 -0.3 7.1 6.7
Latin America and the Caribbean -1.4 47.7 45.0 -0.9 29.0 27.4
World total -30.3 1.3 -39.0 -1.9 0.1 -2.4
Source: Authors' World Bank LINKAGE model simulations
35
Table 13: Impact of full liberalization of global merchandise trade on indexes of real export
and import prices
(Change in export and import price in 2015 relative to baseline, percent)
Export prices Import prices
Ag & All Ag & All
food merchandise food merchandise
Australia and New Zealand 4.5 2.2 2.0 0.1
EU 25 plus EFTA 1.0 -0.1 -0.1 -0.4
United States 10.1 0.5 1.5 -0.4
Canada 2.4 -0.3 3.4 -0.2
Japan -5.0 0.9 1.6 0.0
Korea and Taiwan -14.9 0.8 5.0 0.2
Hong Kong and Singapore 1.6 1.8 2.0 0.2
Argentina 2.8 2.9 3.3 0.3
Bangladesh -6.5 -5.5 5.9 0.7
Brazil 6.0 3.0 2.6 -0.2
China -0.2 -0.3 7.4 1.0
India -3.5 -6.1 5.0 0.1
Indonesia 1.8 0.5 8.0 1.3
Thailand 2.5 -0.2 1.4 0.1
Vietnam 4.8 -0.8 3.7 0.3
Russia -2.7 -1.9 4.8 0.2
Mexico 1.7 -1.5 8.3 0.3
South Africa -0.6 -0.1 1.6 -0.3
Turkey -0.5 -0.4 9.0 0.0
Rest of South Asia 0.2 -2.1 3.8 0.1
Rest of East Asia 0.3 -0.1 3.6 0.6
Rest of LAC 2.0 -0.3 3.5 0.1
Rest of ECA -2.6 -2.5 1.8 -0.8
Middle East and North Africa -1.0 -1.8 4.5 0.1
Selected SSA countries 2.6 1.4 1.5 -0.6
Rest of Sub Saharan Africa -1.4 -3.1 3.7 -0.1
Rest of the World 0.1 -0.5 -0.8 -0.3
High-income countries 3.2 0.3 0.9 -0.3
Developing countries 1.2 -0.8 5.0 0.4
Middle-income countries 1.7 -0.6 5.2 0.4
Low-income countries -0.1 -2.2 4.1 0.3
East Asia and Pacific 1.6 -0.2 6.2 0.8
South Asia -2.7 -5.1 4.8 0.1
Europe and Central Asia -2.2 -1.8 4.2 -0.3
Sub Saharan Africa -0.4 -1.5 3.0 -0.2
Latin America and the Caribbean 3.1 0.0 4.8 0.1
World total (excluding intra-European trade) 3.9 0.1 3.1 0.0
Source: Authors' World Bank LINKAGE model simulations
36
Table 14: Impact of full global liberalization on output, value added and exports of cotton,a
by region, 2015
(2001 $ billion)
Cotton Value added Cotton
output in cotton exportsb
production
United States -4.7 -2.8 -3.5
EU 25 plus EFTA -1.4 -0.5 -1.0
Other high-income 1.0 0.4 0.9
Sub-Saharan Africa 2.2 1.1 1.9
Latin America 1.2 0.6 0.7
Other developing 1.8 0.4 1.6
World total 0.1 -0.7 0.6
aActually all plant-based fibers, but cotton is more than 95 percent of that sector.
bIncluding intra-EU trade
Source: Authors' World Bank LINKAGE model simulations
37
Table 15: Shares of the global cost of agricultural and processed food protection
attributable to specific products, 2015
(per cent)
Rice 20
Sugar 18
Meat products 16
Coarse grains 9
Oilseed products 7
Dairy products 5
Wheat 2
Other (including beverages and tobacco) 23
TOTAL 100
Source: Authors' World Bank LINKAGE model simulations
38